POS0893 FACTORS TO CONSIDER FOR MEASURING THE EFFECT OF LUNG FUNCTION ON PATIENT REPORTED OUTCOMES IN SYSTEMIC SCLEROSIS PATIENTS: ANALYSIS OF THE EUSTAR DATABASE.
Authors: M. G. Lazzaroni, M. Wilson, E. Hensor, J. H. W. Distler, G. Cuomo, E. Siegert, U. Müller-Ladner, Y. Allanore, M. J. Salvador, B. Anic, U. Walker, L. Czirják, C. Ribi, C. M. Tanaseanu, A. Gabrielli, A. M. Hoffmann-Vold, O. Distler, F. Del Galdo
Journal: Annals of the Rheumatic Diseases (2022)

Background Patient Reported Outcomes (PROs) are central to measure how patients feel and function especially when determining the effect of disease modifying agents. In patients with Systemic Sclerosis associated Interstitial Lung Disease (SSc-ILD), dyspnea is the main driver of HAQ decline but the effect of reduced lung function on both generic and specific measures of functional impairment is not well defined, and there are many potential confounding biases that could distort the apparent extent and direction of this relationship. Moreover, collider biases potentially induced by selection into the cohort and in clinical trials can also play a role. Objectives To define within the EUSTAR database, the correlation of Forced Vital Capacity (FVC) and functional impairment PROs and identify potential confounders to be considered in casual inference studies. Methods A cross-sectional analysis included for each patient with SSc-ILD (by X-ray and/or HRCT) in the EUSTAR registry the last visit with at least one PRO (Health Assessment Questionnaire Disability Index [HAQ-DI], Cochin hand function scale [CHFS] and/or dyspnoea visual analogue scale [VAS]) and % predicted FVC (%pFVC), if available. Patients with LVEF≤50% or pulmonary arterial hypertension at RHC were excluded. SSc-ILD with restricted lung volume was defined as %pFVC≤70 [1]. Spearman’s correlation analysis was performed. Results of this analysis and literature review were integrated to design a directed acyclic graph (DAG) and identify the appropriate confounder adjustment set for the total causal effect of FVC on functional impairment PROs. Results Among 17.338 SSc patients in the EUSTAR registry (extracted in November 2019), 727 SSc-ILD patients fulfilled the inclusion criteria (median %pFVC 90 (IQR 74-104), median %pDLCO 60 (IQR 47-52)). Patients with %pFVC&lt;70 (n=149), as compared to those with %pFVC≥70 (n=578) had worse HAQ-DI, CHFS and VAS-dyspnoea scores (Table 1). In unadjusted analysis, %pFVC showed a weak correlation with HAQ-DI (r=-0.21) and CHFS (r=-0.17), but a stronger correlation with VAS dyspnoea (r=-0.33). Table 1. Results are reported as number/number available (%) for dichotomic variables, or as median (IQR) (n available) for continuous variables. %pFVC≥70 (n=578 ) %pFVC&lt;70 (n=149 ) Age at disease onset (years ) 60.6 (52.3-69.3) (546) 52.5 (45.6-63-7) (137) Disease duration (months ) 134.4 (77.5-212.2) (546) 110.3 (66.3-199.7) (137) Male sex 84/578 (14.5) 32/149 (21.5) Anti-Scl70+ 231/468 (40.7) 81/122 (66.4) Smoker ever 52/389 (13.4) 17/107 (15.9) Caucasian ethnicity 545/569 (95.8) 131/145 (90.3) dcSSc 167/559 (29.9) 74/147 (50.3) Oesophageal symptoms 319/571 (55.9) 93/147 (63.3) Muscle weakness 78/565 (13.8) 37/149 (24.8) CRP elevation 141/540 (26.1) 53/134 (39.6) Elevated sPAP (ECHO ) 45/456 (9.9) 21/121 (17.2) Pericardial effusion 2/448 (0.4) 4/110 (3.6) Diastolic function abnormality 151/431 (35.0) 31/102 (30.4) Conduction blocks 78/480 (16.3) 35/120 (29.2) %pDLCO 62 (52-74) (527) 42 (35-53) (118) CHFS 7 (1-23) (493) 16 (2-34.8) (114) HAQ-DI 0.63 (0.13-1.13) (578) 1.25 (0.38-2) (139) VAS dyspnoea (0-100 ) 15 (10-45) (391) 40 (20-70) (109) NYHA stage 3/4 47/561 (8.4) 37/143 (25.9) Subsequently, we created a DAG showing the proposed causal pathway considered relevant to the relationship between FVC and HAQ (Figure 1). Conclusion Lung function as measured by FVC appears to correlate with worse patient-reported function in our unadjusted analysis of the large multicentre EUSTAR dataset. However, to estimate the total causal effect we must consider a multitude of potentially confounding factors, which need to be integrated and analysed in a causal inference framework. The proposed DAG will inform the development of simulations of the potential impact of bias (confounding, collider and omitted variable) on effect estimates we could obtain from EUSTAR cohort. References [1] Goh NS, et al. Am J Respir Crit Care Med, 2008. Disclosure of Interests Maria Grazia Lazzaroni Grant/research support from: Research grant from Boehringer-Ingelheim, Michelle Wilson Grant/research support from: Research grant from Boehringer-Ingelheim, Elizabeth Hensor: None declared, Jörg H.W. Distler: None declared, Giovanna Cuomo: None declared, Elise Siegert: None declared, Ulf Müller-Ladner: None declared, Yannick Allanore: None declared, Maria Joao Salvador: None declared, Branimir Anic: None declared, Ulrich Walker: None declared, László Czirják: None declared, Camillo Ribi: None declared, Cristina-Mihaela Tanaseanu: None declared, Armando Gabrielli: None declared, Anna-Maria Hoffmann-Vold: None declared, Oliver Distler: None declared, Francesco Del Galdo: None declared